In most major countries, daily case growth has switched from exponential to linear, an important first step towards the infection being under control. See https://ourworldindata.org/grapher/daily-covid-cases-3-day-average for more, you can change which countries are on the graph for more detail. The growth rate in the world as a whole has also turned linear, https://ourworldindata.org/grapher/daily-covid-cases-3-day-average?country=USA+CHN+KOR+ITA+ESP+DEU+GBR+IRN+OWID_WRL . Since this is growth per day, a horizontal line represents a linear growth rate.

If it was just one country, I would worry it was an artifact of reduced testing. Given almost every country at once, I say it's real.

The time course doesn't really match lockdowns, which were instituted at different times in different countries anyway. Sweden and Brazil, which are infamous for not taking any real coordinated efforts to stop the epidemic, are showing some of the same positive signs as everyone else - see https://ourworldindata.org/grapher/daily-covid-cases-3-day-average?country=BRA+SWE - though the graph is a little hard to interpret.

My guess is that this represents increased awareness of social distancing and increased taking-things-seriously starting about two weeks ago, and that this happened everywhere at once because it was more of a media phenomenon than a political one, and the media everywhere reads the media everywhere else and can coordinate on the same narrative quickly.

New post by Tomas Pueyo, the author of 'Coronavirus: The Hammer and the Dance':

'Coronavirus: Out of Many, One'

Here’s what we’re going to cover today, with a lot of data, charts and sources:
1. What’s the situation in the US and its states
2. Why the coronavirus should be a bipartisan issue
3. The economics of controlling the virus
4. Which decisions should be left to the federal government or to states

Here’s what you’ll take away:

The coronavirus is growing everywhere in the US.
Some states are on their way to controlling it.
Others have massive outbreaks that make China’s outbreak pale in comparison.
Many are unprepared, and will suffer some of the worst outbreaks.
All voters care about this, Democrats and Republicans.
Democrats were hit first.
But Republicans have more to lose.
They’re older and more likely to die.
Most hesitation comes from the perceived cost of suppressing the virus.
Fortunately, it’s cheaper to suppress it than to let it run loose.
We should do it.
But right now, states are left fending for themselves. It’s a mess.
They are competing against each other instead of collaborating.
They might be forced to seal their borders with each other.
There is a role for states and a role for the federal government. The federal government coordinates, the states execute.
If both step up, we will save lives and increase the GDP.

[EDIT: Bucky points out that these cases make up too high a proportion of new cases for novel reinfection to be the primary mechanism, which means that there's negligible evidence to move the basic prior that general immunity should persist for a while (once the virus is well and truly defeated by the immune system).]

In South Korea, 2% of previously recovered patients have again tested positive and are again in isolation. There are several other explanations besides a general lack of acquired immunity (which would be the worst possible case, from a public health standpoint). But it seems critical that someone look at the evidence for the most dangerous possibility.

There's a fascinating post by Patrick McKenzie (software engineer at Stripe, American living in Japan) on the Covid-19 situation in Japan.

With others, he did independent research into the issue when public sentiment stated the virus was well under control. They circulated this research privately and publically (anonymously), and the story even involves a cryptographic hash to pre-register their research (reasoning).

The whole post is interesting, and contains this gem that reminded me of LW concepts like a Crisis of Faith or Yudkowsky's Civilizational Inadequacy:

I know the exact moment that I got worried for Japan: [...]

I didn’t do anything major, for a while.

I assumed everyone in a position to act had reached this conclusion. Surely, talented epidemiologists understand exponential growth and already know the shape of things to come. Surely, there is a department of people working day and night on the national response effort. Surely, all professionals understand how to parse official communications. Surely, in a hundred thousand rooms, responsible professionals have told their leadership what would soon happen. Surely, in a hundred thousand rooms, people in positions of authority have pulled out a thick red binder, steeled their hearts, and gone to work.

And so I mostly focused on the situation abroad, worrying for family and friends. I tried to distract myself with work. Then, by complete happenstance, two very smart people in one day told me that they believed the public consensus.

Japan was weathering the coronavirus situation well. I was lucky to be in Tokyo.

Imagine how surprised you would be if someone turned into a cat in front of you. That was how surprised I was.

I immediately attempted to update them on my understanding and reasoning for it, assigning an 80% probability to Japan (and Tokyo specifically) following the experience of peer nations. I suggested they orient their organizations consistently with that.

And then I looked at the behavior of people in the world, really looked, and suddenly had the terrifying thought that maybe many did not know.

I think the post may be of sufficient interest to LWers that it could warrant a top-level post, but I don't know how to make such a post a valuable one. Consider this an invitation to this effect.

I've seen an image on social media that suggests postural drainage, a physical therapy practice used mostly for cystic fibrosis, as a way to cope with COVID-19 at a sub-hospitalization stage; the shared image suggests that draining the mucus can keep a patient from needing a ventilator. (I'll transcribe the actual text attached to the image in a subthread, but it's of pretty low quality; I've written here what I think is the only interesting point.)

Unfortunately, Googling "postural drainage coronavirus" just gets me all the medical pages on postural drainage (because they now have headers about coronavirus).

It's a very cheap intervention for patients not on ventilators, the mechanism seems at least plausible, and it's the sort of thing that medical professionals might fail to consider. Is it worth taking a closer look?

Thanks for the shout-out, but I don't think the thing I proposed there is quite the same as hammer and dance. I proposed lockdown, then gradual titration of lockdown level to build herd immunity. Pueyo and others are proposing lockdown, then stopping lockdown in favor of better strategies that prevent transmission. The hammer and dance idea is better, and if I had understood it at the time of writing I would have been in favor of that instead.

(there was an ICL paper that proposed the same thing I did, and I did brag about preempting them, which might be what you saw)

Some points from an interview with virologist Hendrik Streeck who is leading a systematic study in the German town of Gangelt in the county of Heinsberg, one of the epicenters of Corona in Germany (https://www.zeit.de/wissen/gesundheit/2020-04/hendrik-streeck-covid-19-heinsberg-symptome-infektionsschutz-massnahmen-studie/komplettansicht, ZEIT online, April 6, interviewed by Jakob Simmank and Florian Schumann):

• The team is testing, for the first time, a representative sample (1,000 from 500 households) for Germany on whether they are infected with Corona virus (smear test and antibody blood test).
• There was a famous carnival event in Heinsberg and in Germany it is kind of common knowledge by now that the large outbreak in Heinsberg can be traced back to that event. In the study, people were asked whether they attended that event, whether they had pre-existing conditions or take any medications; and all participants of that event were finally tested, and the researchers are reconstructing who sat next to whom and talked to whom. People had assumed that infection had spread via insufficiently clean draft-beer glasses; this seems to be wrong, most people had bottled beer. Moreover, people got ill a day or so after the event, which does not fit the incubation time. There is a school nearby in which seemingly almost all pupils and parents were ill in January. These people are now tested for antibodies.
• In February, during the initial breakout in Heinsberg, the homes/apartments/houses of infected people where tested, and this is now done for newly infected as well. This includes taking air samples and samples from remote controls and door knobs. Up to now: 70 households, but they are planning for a larger sample.
• They found viruses on things or door knobs and (once) in toilet water when somebody had diarrhea, but not once did the researchers succeed in breeding intact viruses from these samples. This suggests that most people are not infected via surface viruses.
• The team had been among the first to find loss of taste and smell as a symptom. Now the data shows that about a third of patients have diarrhea, sometimes for several days, which is more than was assumed. Moreover, Streeck says his team heard from somewhere else several times (but not yet found in their own samples) that people report of deafness and dizziness. He says that these are things nobody originally paid attention to because they do not fit a respiratory disease. The interviewers note that it fits reports of headache and other nerve-system symptoms including findings of brain damage in the case of deceased patients (https://pubs.rsna.org/doi/10.1148/radiol.2020201187). Streeck notes that Sars-CoV-2 is a surprising virus and mentions a two-phase pattern (pharynx first, lung later). He also mentions that authors of another study found the virus in blood samples, while the Heinsberg researchers did not find that among their 70-person sample (and that it could be possible that the virus only enters the blood in severe cases, but not the mild ones).
• Both from Heinsberg and from other cases, Streeck states that infection mostly seems to happen via relatively close contact (he mentions that transmisisons of/via haircutters, taxidrivers etc did NOT seem to happen in one famous and well-researched case in Munich, but that basically the whole network of infection can be often be reconstructed).
• He notes that sitting in your apartment and not getting any sun is bad for your immune system, and curfew-like restrictions and behavioral recommendations should be more evidence-based.

I've written a blog post on "Body Mass and Risk from COVID-19 and Influenza", available at https://radfordneal.wordpress.com/2020/04/06/body-mass-and-risk-from-covid-19-and-influenza/

Here's the intro:

Understanding the factors affecting whether someone infected with COVID-19 will become seriously ill is important for treatment of patients, for forecasting and planning, and — with factors that can be changed — for personal decisions aimed at reducing risk. Despite our current focus, influenza also remains a serious disease, so understanding its risk factors is also important.

Here, I’ll look at some of the evidence on how body mass — formalized as Body Mass Index (BMI, weight in kilograms divided by squared height in metres) — influences prognosis for respiratory diseases. Information specific to COVID-19 is still scant, but there is more data on influenza and on other respiratory infections (which includes coronaviruses other than COVID-19). Information on how BMI relates to general mortality should also be helpful.

Below, I’ll look at two relevant papers, plus a preliminary report on COVID-19. To preview my conclusions, it seems that being underweight and being seriously obese are both risk factors for serious respiratory illness. Furthermore, it seems that “underweight” should include the lower part of the “normal weight” category as defined by the WHO. Official advice in this respect seems dangerously misleading.

• A laboratory study (preprint) showed that covid could live in cat and ferret respiratory systems, but not dogs, pigs, chickens, or ducks. It further found that covid could be passed to from an infected to an uninfected cat in an adjacent cage (doesn't look like they tested transmission in ferrets).
• A survey (preprint) of Wuhan cats indicated 15% of cats surveyed after the outbreak had antibodies to covid. 0 of 39 cats caught before the outbreak had antibodies. (ETA 4/9: They don't mention what they were sampling from, from what they imply I think 15% is an overestimate but still enough to establish the possibility).
• At least one zoo tiger has test-confirmed covid, and several big cats at the zoo are showing symptoms

So it seems pretty likely cats are vulnerable to covid, and may be able to pass it to humans.

https://en.wikipedia.org/wiki/Pneumocystis_pneumonia

Could the coronavirus be interfering with the immune system in a way that is allowing Pneumocystis pneumonia to thrive?

My understanding is that Pneumocystis pneumonia, otherwise known as PJP or PCP, is caused by a fungus. It is highly opportunistic, and is rarely seen in people with healthy immune systems. It is highly associated with AIDS/HIV.

The fungus that causes it is widespread, and likely exists in the lungs of most healthy people.

I'm not sure about this one, but it seems relatively difficult to test for. Given it's rarity, it seems it is most are assumed to have it if they present symptoms and are positive for HIV/AIDS. If they are suspected, it seems they test for HIV/AIDS first.

Symptoms sound similar, if not the same as coronavirus

CT scans of those suffering from coronavirus and PJP are very similar, and both are very different from more typical pneumonia.

I have seen some papers that indicated the coronavirus may lower CD4 T-Cell counts, which is one of the reasons PJP is seen in HIV/AIDS patients. Not sure if this has been well studied and peer reviewed yet.

There exists a very effective treatment for PJP, Bactrim.

I could see how this might be overlooked given its rarity. Also I am not sure how much experience China has with HIV/AIDS and PJP. I also not an expert, and this might look foolish to someone who is more knowledgeable. I hope that person is out there and can weigh in.

Hydroxychloroquine update!

A smart friend pointed me to this study that explains that mediocre antivirals only work if administered right after infection. By the onset of symptoms the effect is already much reduced. (The study isn't clear as to what counts as "symptoms" except that they occurred 3 days before hospitalization, so maybe early warning signs like loss of smell don't count). HCQ is, at best, a mediocre antiviral.
https://www.medrxiv.org/content/10.1101/2020.04.04.20047886v1

This model agrees with a new study from China (N=150) that showed zero effect when giving patients HCQ 16-17 days after the onset of the disease. Of note, the study compared Standard of Care to SOC+HCQ, and I have no idea what the Chinese SOC is beyond the minimal requirement of intravenous fluids, oxygen, and monitoring that's mentioned in the paper. In particular, there's no info on whether it includes antibiotics like azithromycin, and whether it includes zinc. It's hypothesized that HCQ works partly by easing the entry of zinc into cells where it slows viral replication, and so they work well in conjunction.
https://www.medrxiv.org/content/10.1101/2020.04.10.20060558v1

Bottom line: it may still be worth it to take HCQ+zinc if you cough and lose your sense of smell two days after going through an airport, but HCQ may not be of any help to heavily symptomatic people (and it still has nasty side effects).

Real bottom line: now that hydroxychloroquine is a politicized issue, you can't trust anything journalists have to say about it and have to read the studies yourself.

Scott talked some days ago about how Brazil didn't take real coordinated efforts, and as a brazillian living in the country's largest city, I'm here to both defend my country and say that things are much worse than a lack of coordination.

The government, both at federal and state level, took quarantine measures earlier than other countries did (according to the Johns Hopkins institute), compared to number of confirmed cases. We officially closed schools at about 100~ confirmed cases, with parents refusing to take their kids to school much earlier. (Per comparison, Lombardy closed at about 200 cases or so).

They're also taking measures to have a semi-UBI going on so people have spending money for basics and utilities. Brazil also has much more robust work laws than US, thus people aren't at such a risk of sudden unemployment without social safety nets that can last them through this pandemic. They're also pushing for landlords and companies to open negotiations for rent and utilities.

BUT

The biggest factor here is the brazillian people, which are simply not caring about what the media has to tell them. Barely two weeks of quarantine in, and people are going outside and finding ways to restart their normal convenient lives.

Stores will open and work normally, but restrict the number of clients inside, thus forcing people to wait in long queues on the sidewalks (which is legally public and thus the store can't be blamed for gathering people despite the current quarantine orders going on. Also for cultural reasons, no one is going to give the 5ft space recommendation. All the queues are as dense and closely packed and near the entrance as they can get away with).

During weekends, people will still throw large illegal parties (baile funk) or go outside to walk in parks, eat street food and unwind under the sun or on our beaches.

I believe that a reason this is happening is because people here largely distrust the media and will prefer to receive their news from chain messages on Whatsapp(Page 122). Thus misjudging the risk or severity of the situation. Another root cause might be risk compensating behavior; since everyone is now washing their hands and using alcohol gel and taking care to not cough on others, thus is safe to go outside and behave normaly if everyone is taking these precautions.

Bonus point: Who has a very dense public transport system and a city population higher than NYC and close to Tokyo's thus making any attempt of "social distancing" very moot? Yes, Brazil.

This is going to be quite a ride for most of us.

I've been playing with the Kinsa Health weathermap [LW · GW] data to get a sense of how effective US lockdowns have been at reducing US fever. The main thing I am interested in is the question of whether lockdown has reduced coronavirus's r0 below 1 (stopping the spread) or not (reducing spread-rate but not stopping it). I've seen evidence that Spain's complete lockdown has not worked so my expectation is that this is probably the case here. Also, Kinsa's data has two important caveats:

• People who own smart thermometers are more likely to be health conscious which makes them more likely to be health conscious than the overall population. Kinsa may therefore overstate the effect of the lockdown by not effectively sampling the health apathetic people more likely to get the virus.
• Kinsa data cannot separate coronavirus fever symptoms with flu fever symptoms. At the early stages of coronavirus spread, seasonal flu illness dominates coronavirus illness and seasonal flu r0 is between 1-2. This means that a lockdown can easily eliminate symptoms caused by seasonal flu illness by reducing flu r0 below zero without reducing coronavirus's r0 below zero.
• I'm addressing this by comparing the largest amounts of observed atypical illness over the last month in different locations with their current total illness to get a conservative estimate of how much coronavirus %ill have changed.

With this in mind, my overall conclusion is that the Kinsa data does not disconfirm the possibility that we've reduced r0 below 1. Within the population of people who use smart thermometer's, we've probably stopped the spread but it may/may not have stopped in the overall population. Here are my specific observations:

• The overall US %ill weakly suggests we may have reduced r0 below 1. It maxed out at around 5.1% ill compared to a range of 3.7-4.7 %ill . This indicates that 0.4-1.4% of overall illness was due to coronavirus and currently total illness is only 0.88%. This means that, for many values in that range, our lockdowns are actually cutting into the percent of people getting coronavirus and therefore that the virus is not growing.
• New York county NY %ill weakly suggests that we may have reduced r0 below 1. It maxed out at 6.4 %ill compared to a typical range of 2.75-4.32, indicating that 2.1-3.65% of people had coronavirus. Currently, total illness is 2.56%. Again, for most values in that range, it looks like we're reducing the absolute amount of coronavirus.
• Cook county IL (Chicago) %ill is very weakly positive on reducing r0 below 1. It maxed out at 5.4 %ill with a range of 2.8-4.9 indicating that 0.5-2.6% of people had coronavirus. Currently the total is 0.92% which suggests we've likely cut into coronavirus illness. The range of typical values is so large though that its hard to reach a conclusion
• Essex country NJ (Newark) %ill doesn't say much about r0. It maxed out at 6.1 compared to a typical range of 2.9-4.5 which implies a range of coronavirus %ill of 1.6-3.2 The current value is 2.63% which is closer to the higher end of the range so there's no evidence that we've reduced the amount of coronavirus. Still %ill is continuing to trend down so this may change in the future.
• I also considered looking at Santa Clara County CA, Los Angeles County CA, and Orleans Parish LA (New Orleans) but their %ill never exceeded the atypical value by a large enough amount for me to perform comparison.
• On Mar28, the overall US %ill changed from a steep linear drop of ~-0.3%ill/day to a weaker linear drop of ~-0.1%ill/day. Also, on Mar28, both Newark's and New York's fast linear drop is broken with a slight increase in illness and it looks like we're on our second leg down there now. Similar on Mar27, Chicago's fast linear drop is broken with a a brief plateau and second leg down. No idea why this happened.

I'm personally quite worried about disruptions to the food supply chain severe enough to cause food shortages in e.g. the Bay Area in the next few months but not sure what to do with that worry other than to stock up more on non-perishables. Would very much appreciate seeing more people thinking and researching about this.

Summarizing an article on gloves: https://www.n-tv.de/panorama/Einweghandschuhe-so-wichtig-wie-Masken-article21689035.html (April 2)

First, about virus survival on surfaces in general:

Germany's (kind of celebrity) virologist Christian Drosten's (Berliner Charité hospital) opinion on the study about survival rates of Sars-CoV-2 on surfaces and the possibility of smear infection:

He hypothesizes that for the experiment, dass für den Versuch Viruses in a larger drop were put on the surface, and even though in this way you can verify infectiosity even after hours, probably only very few viruses survived. On fingers, the amount of viruses decreases further and gets into contact with the acidic milieu of the skin, and it is unclear whether anything remains; similarly simple experiments cannot simulate that. The German federal institute for risk assessment states that it currently does not know of Sars-CoV-2 infections via touching surfaces.

Note that I neither checked the statements cited, nor the sources; this is simply a translation and summary of a paragraph from the article. Starting from this, the article writes about disposable gloves.

The article states that gloves are of course considerable but that you of course should not touch your face with the gloves, and that it should also be considered that Sars-CoV-2 viruses seem to survive longer on plastics etc than on skin, that also bacteria thrive on gloves more than on hands and gloves distribute them more than hands do. Moreover, if you wear them for a longer time, the skin sweats and swells, which opens an entry to the body for viruses and bacteria. Finally, taking the gloves off without touching them is not as easy as you might think, and disposing them should of course be done properly, some people just leave them in the shopping cart.

The article basically recommends to prefer washing your hands and not touching your face over using disposable gloves. It also kind of suggests that gloves can be the opposite of face masks in one sense: Simple face masks do protect other people, while gloves may even make matters for other people worse.

The Imperial college model (yes, that one) has just been released, open-source, for anyone to look at. We don't actually know what the model's precise projections were (thanks to the UK governments lack of transparency), but we do know that ever since the UK's lockdown was declared the model had been predicting a peak on Easter weekend, which was, in fact, what happened in the UK. Imperial supposedly has the best infectious disease modellers in the world, and this is the code of the model that led the UK to dramatically reverse course, so its probably pretty accurate. Here's the GitHub.

I might later write a more indepth post, but for now the core idea. Controling a building to have between 50% and 60% humidity might reduce the amount of spread of corona. There are multiple studies that you can reduce the spread of infections in schools and hospitals that way.

There was also a paper out that suggested COVID-19 to spread less in climates with high moisture and temperature.

If anyone wants to collaborate with me on writing a post about this, please contact me.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4420971/ is skeptical of cloth masks. Does anyone have any thoughts on it, or know any other studies investigating this question?

Should there be a non-coronavirus Open Thread?

Some potentially useful numbers I've been working on estimating:

1. The number of days lag between registered cases and deaths

2. The adjusted CFR for each country taking this into account

The method is essentially to try different lags (dividing current deaths by cases from x days ago) and see which length of lag gives a constant CFR over time (normally CFR increases with time as the growth rate of cases slows earlier than that of deaths).

Here are the results for a few countries:

China: 9 day lag, CFR=4%

USA: 7 day lag, CFR=6.5%

Italy: 4 day lag, CFR=14.5%

Spain: 2 day lag, CFR=10.5%

Germany: 10 day lag, CFR=3.5%

France: 10 day lag, CFR=24%

Switzerland: 6 day lag, CFR=4%

UK: 4 day lag, CFR=18.5%

I'm not sure about these, especially UK but they do create nice constant values for CFR over a period of 2-4 weeks (UK only 10 days) which suggests a predictable pattern, despite variation in testing.

The France result is also not quite as consistent as the others and is surprisingly high so I don't quite trust it either. I could make a case that for an estimate of 7 day lag and 20% CFR.

Interesting COVID-19 vaccine development landscape publication in Nature.

Metaculus is running a competition for accurate, publicly-posted, well-reasoned predictions about how COVID-19 will hit El Paso, Texas, in order to help the city with its disaster response. The top prize is $1,000.

Dr. Birx said in the press conference today that the US is counting any patient who dies with COVID-19 as dying of COVID-19. Are deaths during pandemics normally counted this way? Is it legitimate to call this number inflation--i.e., is there something fishy going on here--or is this standard practice?

Cardboard and plastic: Tottori Prefecture goes low-tech to protect officials from COVID-19

This made my day.

• Cheap, low-tech prevention measures.
• ‘“I hope this system will send out a message that even Tottori, where no infections have been reported yet, is being very vigilant.”’ – Yes!

I want Tottori spirit everywhere.

Is the Chinese coronavirus data fake?

If so, what's a good estimate of the actual number of Chinese cases & actual number of Chinese deaths?

Hi all,

Does anyone know why US cases and deaths tend to be lower on Sundays and (especially) Mondays, compared to other days of the week? Is it something with the timing of how the data are processed?

I put up some quick plots here:

https://twitter.com/Nick_Lutsko/status/1254067996990959616

Apologies if this has been explained before and I missed it.

What should be the relative importance of natural herd immunity vs vaccination, in anti-corona strategy?

Scott Atlas argues that mass isolation prolongs the problem by delaying natural herd immunity. Meanwhile, countries like Australia and New Zealand have engaged in national isolation as well, creating entire national populations where natural immunity will be rare.

Will we see the world divided between countries that rely on natural herd immunity, and those which rely on the artificial herd immunity of vaccination? Does it make sense to have a differentiated strategy within a single country, with natural herd immunity encouraged in some subpopulations but not others?

There are also time issues here: vaccines don't exist yet or are not available in large quantities; and coronavirus immunity may fade out after a year or two.

I assume these issues have been discussed somewhere, and would even be part of public health strategies for well-known diseases like the flu, but I seem to have overlooked such discussions.

P.S. I am looking for nuance, something about the appropriate relative importance of natural versus artificial herd immunity.

Hi,

I need your input on something. Sweden, as many of you know they are going for the herd immunity. Choosing to walk an unorthodox way.

They are still only reporting around ten thousand cases but with a death toll of 600 and rising. Probably the true number of infections is around 40k-100k depending on what mortality/asymptomatic cases we assume. The current rate, as in the number of hospitalizations per day is still within the the limits. It could probably go as high as double the death rate, before breaching the limit.

To reach heard immunity they need 60% of population (10 million) immune I'm told, with the other important goal of not breaching the capacity of the healthcare system.

With some calculations we could land on the maximum rate of infections of say 10k per day, before our healthcare starts to break apart. The exact figure is not important, the approximate magnitude is. With 10k infections per rate, Sweden would need 600 days to develop her immunity.

Recently some info from Denmark has indicated 27/1000 blood donors have tested positive for antibodies in one population and 0/244 in an other. I can share the source (Danish) unfortunately not much details on type of test or other information. But this has me wondering if you sit on any information of corona virus test false positives. cellax seems to.be around 1.5-3%

In case herd immunity, is the way to go having potentially tens of thousands of asymptomatic cases is great news as a tenfold increase in actual infections coupled with the current death rates will give Sweden a time to herd immunity of only a few months.

Of course percentage required would go up as R0 in that case is a little higher than what we initially thought.

From what I've read from other studies this is unlikely and herd immunity is as far away as the (winter) Olympics.

Anyways what are your thoughts? do you happen to sit on some data on false positive rates for various tests?

Video explaining the Czech Republic's experience of having everyone make home-made masks in about 10 days, from a starting point of almost no masks being worn in public in the country.

Here is their COVID19 infection curves on a log chart (seems to be flattening).

With noticeably different governance and social reactions in different locations, I wonder if this situation will spur migration in the coming few years. At what point is it worth moving to somewhere with more sane (still broken; nowhere is perfect) government and social behaviors, even if it's more distant from your personal networks?

Seattle and the Bay Area are looking pretty good compared to New York and Florida (this could reverse over the next few months, but it's unlikely that by end of year there'll be no difference in terms how we evaluate their reactions and outcomes).

Similarly for urban vs more spread-out locations. Especially as many of us learn that we CAN be fairly productive anywhere there's internet service, I wonder if more of us will opt to be around fewer strangers standing so close all the time.

I predict not much movement - people have a learned helplessness about governments, and easily forget that they have choices. And the advantages of cities remain powerful. And, importantly, most people don't actually have quite as much future financial and social freedom as LW readers tend to.

Late Edit: Pangolins with this viral infection have been found from smuggled ones from both Guangxi and Guangdong provinces, but do not show up in wild pangolin populations in general.

Despite the virus being characterized in pangolins, after looking into this, I now think it is basically incorrect to think of this as primarily a "pangolin virus." The pangolins were a dying canary in a coal mine, and probably caught it from something else that serves as the real reservoir species for this nCOV precursor*.

These pangolins were being smuggled when they were captured by the authorities in Guangxi. They were dying of probably several diseases; they had lesions in their skin, intense congestion, and were in generally atrocious condition when they got sequenced for viruses. They turned up positive for all manner of things (herpes out the wazoo, but also a sendai virus which was most closely related to the sequence of a human-taken sample, a paramyxovirus, and yes, several coronaviruses).

Here's the original article on the pangolins whose virome they sequenced, and the article noting its relatedness to nCOV.

Given that so many of the pangolins died, the pangolins look more like a highly-susceptible secondary species, than a mostly-asymptomatic primary reserve species* to me.

* GD/PIL or GD/P2S is thought of as a possible nCOV progenitor, alongside bat-virus RaTG13. GD/PIL's receptor-binding motif (RBM) in particular is identical to SARS-2's, although nCOV otherwise appears more closely related to RaTG13.

** On educated priors, I think the true reservoir is probably rats, bats, or (less likely) humans in the Guanxi, Hunan, and/or Hubei province.

Personally, I assign >90% on either rats (strong priors + skin lesions) or bats (strong priors + simplest story). But these were exotic animal smugglers; there is a small chance that the original reservoir species could be any animal.

I think the brief era of me looking at Kinsa weathermap data has ended for now. My best guess is that that covid spread among Kinsa users has been almost completely mitigated by the lockdown and current estimatess of r0 are being driven almost exclusively by other demographics. Otherwise, the data doesn't really line up:

• As of now, Kinsa reports 0% ill for the United States (this is likely just a matter of misleading rounding: New York county has 0.73% ill)
• New York's trend is a much more aggressive drop than what would be anticipated by Cuomo's official estimate of r0=0.9. [LW · GW]
• None of these trends really fall in line with state-by-state r0 estimates[1] either
• Georgia has the worst r0 estimate of 1.5 but Fulton County GA (Atlanta) has been flat at 0% ill since April 7 according to Kinsa

[1] Linking to the Twitter link because there is some criticism of these estimates: "They use case counts, which are massively and non-uniformly censored. A big daily growth rate in positive cases is often just testing ramping up or old tests finally coming back."

[Years of life lost due to C19]

A recent meta-analysis looks at C-19-related mortality by age groups in Europe and finds the following age distribution:

< 40: 0.1%

40-69: 12.8%

≥ 70: 84.8%

In this spreadsheet model I combine this data with Metaculus predictions to get at the years of life lost (YLLs) due to C19.

I find C19 might cause 6m - 87m YYLs (highly dependending on # of deaths). For comparison, substance abuse causes 13m, diarrhea causes 85m YLLs.

Countries often spend 1-3x GDP per capita to avert a DALY, and so the world might want to spend $2-8trn to avert C19 YYLs (could also be a rough proxy for the cost of C19).

One of the many simplifying assumptions of this model is that excludes disability caused by C19 - which might be severe.

In addition to prediction markets, there are also, y'know, normal financial markets, which implicitly predict lots of things. But I don't personally know how to speak the language. For example, does the market say anything about the price of food, or possibility of shortages, in three months? Like, shouldn't there be some future / option / something whose price corresponds to a prediction about that? Or shortages of other things? Does anyone know?

A US study looking for recruits: NIH begins study to quantify undetected cases of coronavirus infection

A new study has begun recruiting at the National Institutes of Health .... to determine how many adults in the United States without a confirmed history of infection with SARS-CoV-2 have antibodies to the virus.

After enrollment, study participants will attend a virtual clinic visit, complete a health assessment questionnaire and provide basic demographic information—including race, ethnicity, sex, age and occupation—before submitting samples in one of two ways. Participants working at the NIH Bethesda campus will have blood drawn at the NIH Clinical Center. Other volunteers will participate in at-home blood sampling.

Why does recovery data seem so sparse? I only seem to be able to find that data for the global dashboards but that means it should be available. I would think that would be easily found as reporting only deaths is, to be nice, creating a situation where people will be misinformed and overly fearful.

I took a quick look on the links database but nothing jumping out for me there.

New data out of Germany using serological testing found 14 % of the population presented antigens against COVID19. This is massive if nearly 1/7 of the population has already contracted the disease and developed some type of immunity. This is only one piece of data, however, and is even much higher than the Iceland estimates of 50% asymptomatic and 50% symptomatic.

German study

https://www.land.nrw/sites/default/files/asset/document/zwischenergebnis_covid19_case_study_gangelt_0.pdf

Iceland information

https://www.cnn.com/2020/04/01/europe/iceland-testing-coronavirus-intl/index.html

I'm trying to make some educated guess about the situation, but it looks like the data are very lacking. Could someone validate my logic please?

1. Some people claim that SARS-CoV-19 could have been around for ages, "everybody's bad flu last autumn was this thing" and basically nothing is happening except panic. People are dying not because of the virus, but because everybody is going to hospitals making them overcrowded. People dying of other reasons just happen to also have almost-harmless COVID-19. When I've heard this couple weeks ago I chuckled, then gave it a second thought and decided that it could be possible, though unlikely. Now, given we have some antibody tests results (San Miguel County, David Friedberg in SF - 1, 2), we can conclude that "the virus has been around long before Dec 2019" theory is false. Otherwise much more than 1% of people would be positive for antibodies as it is very infectious. Sounds right?

A note. The tests mentioned above are very unreliable (San Miguel county didn't explain the protocol, in the second case the test kits were provided to volunteers who would test their friends or whoever they find appropriate - so non-representative sample by any means). They show that it's not 50% herd immunity, but don't really provide data whether it's 0.01% or 1%.

2. To understand what will happen next, we need to know CFR (Case Fatality Rate) or better yet IFR (Infection Fatality Rate). CFR is deaths / cases, IFR is the same, but tries to account for asymptomatic cases. And that's the problem: we don't know percentage of asymptomatic cases. Maybe 50 people of every 1'000 infected die, and that's 5%, pretty scary. But maybe another 99'000 are also infected, but don't even feel it, then we get 0.05%, less than flu.

I personally watch closely Iceland statistics: https://www.covid.is/data They have a government body testing those in high-risk groups and with symptoms, and a private biotech firm testing everybody. They have conducted about 29'000 tests, 8% of the country population. This data does not contain details about whether those tested had symptoms or not, whether positives developed symptoms later or not etc, but it seems to be the closest to "test big random sample of seemingly healthy population" research I want. 28'992 samples, 1'586 infected, 6 deaths. I feel an urge to count IFR, but it would still be highly inaccurate (there is a skew because partly they test high risk groups, because older age population probably strictly follows isolation and is not exposed, and other factors). Data from Italy, or Diamond Princess cruise ship, or anywhere is very different.

I see two different options here:

1) Low IFR less than 0.5%. Maybe less than flu (~0.1%). It is still dangerous because nobody is immune, and if everybody gets infected at the same time, hospitals are overcrowded and even young patients with typically good prognosis will have complications and die without adequate care. Here we can employ FlattenTheCurve ideas (because majority of cases are mild, don't require hospitalisation and we can "burn through" the population fast), nobody should really worry going for groceries and the quarantine may finish soon.

2) High IFR. It's very dangerous for older generation, it's not nice for younger generation - one will probably not die, but have a reasonable chance of visiting ICU, which is not pleasant. Business as usual, stay at home, wash your hands, wait for a vaccine next year or two.

Which case looks more probable to you? Have you seen any high-quality data suggesting one of the cases? I stress high-quality here, there are lots of reports, but mostly data look unreliable or plainly false.

Thank you.

IHME published a dashboard with state-by-state projections of coronavirus peaks: http://covid19.healthdata.org/projections

The accompanying FAQ is also interesting: http://www.healthdata.org/covid/faqs

Innoculate GI tract with live virus. Suffer GI symptoms. Get immunity. Avoid respiratory complications.

This article and the linked study propose that smokers are getting infected less often due to the nicotine rather than the smoking. Is it worth getting nicotine gum and patches?

Oxford COVID-19 vaccine begins human trial stage

The vaccine is based on an adenovirus vaccine vector and the SARS-CoV-2 spike protein,

I'm trying to formulate a response to, what at least in my circle of friends and acquaintances, is an increasing insistence that people had Covid-19 in November 2019.

If we assume someone did have Covid-19 in upstate NY for instance what else would have to be true?

I think mainly, that a novel virus made its way around the world without detection would be pretty major. And then it mutated in Wuhan, China unleashing this second, more virulent strain, meaning that the pattern of outbreak that we all witnessed beginning in Wuhan was some kind of 'second phase' and not the initial outbreak. It would also mean that current genetic tracing is probably wrong or not accounting for this alleged mutation.

All of this seems very unlikely to me. I don't think I can prove with 100% certainty it is impossible. Even if I could I struggle to understand the emotional attachment people have to the claim that the illness they had was covid-19.

Unknown respiratory disease = Covid-19 strikes me as about as accurate as UFO = Aliens. But people seem to take it very personally when you tell them they could not possibly have had this illness 2months before the outbreak in Wuhan.

Ok, a question of which I assume that people here can quickly provide the answer:

How certain are we that age groups with low likelihood of developing symptoms - in particular, children - are actually infectious? Sure, there is asymptomatic spread in general, but I guess being asymptomatic also correlates with the ability to quickly kill the virus and thus not transfer it to others. So the first question is HOW infectious are people who are and stay asymptomatic? Is there good evidence on this?

Harvard published a study on link between PM2.5 pollution and mortality.

We found that an increase of only 1 μg/m3 in PM2.5 is associated with a 15% increase in the COVID-19 death rate, 95% confidence interval (CI) (5%, 25%)

Places most hit so far are on the more polluted side so one can expect final CFR/IFR be lower than estimated from current data.

Mass testing seems like a promising brute force strategy that can keep R < 1 after lockdown, without requiring contact tracing. I'm pretty early in thinking about this but wanted to share my thoughts to encourage parallel efforts. A few possibilities (not mutually exclusive):

1) RNA testing: If everyone is given a daily RNA test and positives are isolated, transmission will likely be very close to 0. The US is still a factor of 1000 away from doing this (for comparison, RNA testing has scaled by 400x in the last month). However it seems likely that even testing on average every 10 days could keep R < 1. Key questions: i) what frequency of testing is enough? ii) what testing throughput is feasible?

2) Batch RNA testing: To the extent that reagents & machines rather than PPE & workers are the limiting factor in RNA test capacity, batch testing can be used, stopping the binary search at some threshold (e.g. at batch size 10). This of course results in lots of unnecessary isolation but still a small share of the population would be isolated. Key questions: i) are reagents & machines more limited than PPE & workers? ii) what's the optimal specificity / stopping point?

3) Cheap symptom-based tests: Paul Romer has pointed out that even fairly poor tests (with specificity & sensitivity much lower than RNA tests) can significantly reduce transmission without requiring a very large share of the population to be isolated. Fever (present in 85% of mild cases) and anosmia (present in 60% of mild cases) can be tested for very cheaply. Isolating everyone with fever or anosmia eliminates nearly all transmission except for fully asymptomatic transmission. The importance of fully asymptomatic transmission is still pretty uncertain (asymptomatic shedding seems to be important but probably a nontrivial fraction of "asymptomatic" would have a mild fever or anosmia), so this might need to be combined with additional measures.

How much do we know about gender differences?

I saw a reddit thread suggesting that women have different symptoms than men, though it was super anecdotal and I can't find it now. I know women have a lower death rate, and I understand that was originally suspected to be because men smoke more but more recently maybe that turns out not to explain the whole difference? This paper suggests that men have more ACE2 than women, which is the enzyme the virus binds to.

Is this a thread that's been well explored by others?

Something to keep an eye out for:

we also predict that the virus may invade multiple brain tissues, which may help explain to the loss of taste and smell in infected individuals. Has anyone seen evidence of further brain damage in COVID-19 patients? Please share if you do!

Also unexpected is the prediction that the virus may be able to invade the reproductive system (vagina, uterus, testis, cervix, ovary). Has anyone seen evidence for this? Please share if you do.

The COVID-19 targets do not show significant overlap with any major disease module (we tested it against 299 diseases in Menche et al.). The closest diseases to the COVID-19 targets are cardiovascular diseases and cancer, in line with the clinical evidence. Interestingly, we once again find disease of the nervous system among the most proximal diseases

Source

NYT: "Some Coronavirus Patients Show Signs of Brain Ailments"

"The Case for Universal Cloth Mask Adoption & Policies to Increase the Supply of Medical Masks for Health Workers"

Excerpt from Twitter thread summarizing it:

We have very good evidence that universal adoption of cloth masks will combat the spread of the virus. Specifically, we know that 1) asymptomatic people spread the virus, 2) mask wearing by infected people prevents them from transmitting the virus (the report provides citations).

How large are the benefits? Even if masks reduce transmission probabilities by only 10% (and as you'll see, that is likely very conservative), the value of *each cloth mask* is between $3,000 and $6,000. Our best estimate is that their protective value is closer to 40-50%.

These estimates are of course sensitive to the assumptions made in the underlying epidemiological models. But even if those models overstate mortality risk by a factor of TEN, each cloth mask *conservatively* generates $300 in value!

That policy is getting more medical masks to healthcare workers. The same economic argument that says that masks for the average person are worth thousands of dollars suggests that each N95 respirator for a healthcare worker could be worth *millions* of dollars (report says why).

[...]

This is why we recommend universal adoption of *cloth masks*, at least until there is no (domestic or global) shortage of medical masks for healthcare workers. Homemade cloth masks do not interfere with the production of medical masks.

https://www.dropbox.com/s/6ua7j979dbqb045/masks_final_n_HF_NA.pdf?dl=0

Does anyone have any idea / info on what proportion of the infected cases are getting Covid19 inside hospitals? This seems to have been a real issue for previous coronavirus.

I'd say there might be a stark difference between countries / regions in this area. Italian health workers seem to have taken a heavy blow. Also, 79 deaths in Brazil (total: 200) came from only one Hospital chain/ health insurer, which focus on aging customers (so, yeah, maybe it's just selection bias?).

(Epistemic status: low, but I didin't find any research on that after 30min, so maybe the hypothesis deserves a bit more of attention?)

Swiss cardiologist Nils Kucher is going to start a study to check whether blood thinners help covid-19 patients, suspecting that lung embolisms play a role in hospitalization and mortality. (https://www.n-tv.de/wissen/Helfen-Blutverduenner-bei-Corona-Infektion-article21722726.html)

I am not sure how it is possible that there are reports in the media claiming a low IFR (0.1%) when Lombardy has an official population fatality rate (i.e official COVID19 deaths over total population) of 0.12%, and unofficial one of 0.22% (measuring March and April all cause mortality there are ~10000 excess deaths) and a variability of up to 10x of casualties between towns more or less hit, indicating that only a small fraction (~10-20% imho) of the entire population was infected. I am pretty confident that the IFR is around 1% on average: it’s probably lower for younger people (0.2%) but as as high as 3% for people over 65. Moreover, Lombardy average age is less than the Italian average and the same as Germany. Even if there could be some age distribution difference they can’t explain the variation in the estimated IFR.

Hi all. I haven't been to LessWrong in a while...but the mess in the world has reminded me how important it is for us to strive for clear thinking as a community. With that, I'd like to share a Coronavirus pandemic information site that has really good analysis for tracking the progress of the pandemic. It's here: https://ourworldindata.org/grapher/daily-covid-cases-3-day-average

(it seems that I cannot embed or add images)

<iframe src="https://ourworldindata.org/grapher/covid-confirmed-daily-cases-epidemiological-trajectory" style="width: 100%; height: 600px; border: 0px none;"></iframe>

How Large is the Iceberg? New Evidence from Kansas City

The details are currently vague, but I have tried to report key information, as this is one of the few efforts at random sampling that I am aware of. My main hope is to inspire someone with more expertise and ability to access details to expand the analysis.

Basics:
Johnson County, with a population of 602k, has reported on preliminary results from an effort to test a representative sample of its residents. I have been unable to find details about how they constructed the sample, so cannot assess how representative it is likely to be, but at least it's not another dataset that selects on the sick. Out of 369 residents tested via PCR on Friday April 10th, 14 residents tested positive, for an estimated infection rate of 3.8%. The results were discussed at the 4/16 Board of County Commissioners Meeting. The video and slides are generally made available at some point after the meeting at https://boccmeetings.jocogov.org/onbaseagendaonline, but they have not been posted as I write this.

Hazarding to Interpret the Results:
Major Caveats
-I don't know how representative the tested sample is of the Johnson County population.
-I don't know details about the type of test they used, so I am not trying to account for false negatives or false positives.
-The test is not for antibodies, so it does not capture people who were infected and recovered.
-I'm ignoring statistical uncertainty.
-The results are from 6 days ago.
-Deaths and hospitalizations from those testing positive will increase with time.


As of April 16, 343 people have tested positive in Johnson County according to the county's dashboard (available at https://public.tableau.com/profile/mapper.of.the.day.mod.#!/vizhome/covid19_joco_public/Dashboard). Ignoring the major caveats above, there should be 22,800 infections in Johnson County, suggesting that:

Infections are being undercounted by a factor of more than 60.
An estimate of infection fatality rate is .1%.
An estimate rate of admission to ICU is .2%
An estimate of the hospitalization rate (inpatient and outpatient) is 1.6%

Why are surgical or self-made masks supposed to be better at protecting others than at protecting oneself? Naively, it seems to me that the percentage of filtered droplets/aerosol should be the same regardless of the direction in which it is breathed.

Idris Elba and his wife, two weeks after testing positive for the coronavirus, say they still have experienced no symptoms

The pool of people who 1. received a test while asymptomatic 2. tested positive and 3. are updating the public about their condition through mass media seems very small to me. The fact that two of them are turning out to remain fully asymptomatic seems to indicate that this is in fact likely to be a common thing. Somewhat surprising imo.

Seems like a good model for estimating total infections, from my quick look: https://observablehq.com/@danyx/estimating-sars-cov-2-infections

I haven't poked its methodology.

Which US federal agencies should receive more funding in response to coronavirus? Which should receive less?

From the Center for Health Security's covid19 brief:

PANAMA IMPLEMENTS GENDER-SPECIFIC SOCIAL DISTANCING In an effort to further enforce nationwide social distancing measures, Panama recently announced that it is implementing gender-specific rules for when people can leave their homes. Women will be allowed to be outside on Mondays, Wednesdays, and Fridays, and men will be allowed on Tuesdays, Thursdays, and Saturdays. On Sundays, everyone must remain indoors.

More info here. Maybe someone was listening to Scott's surname-based lockdown suggestion.